Great Chart: US ST Yield Curve vs. Cyclical-Defensive Stocks

Lately, the sharp revision of the US annual saving rate (up 1.6% on average since 2010) shifted growth expectations to the upside and lowered the bottom of the unemployment rate for the next few quarters. For instance, Goldman revised its GDP growth to 3% in Q4 (from 2.5% previously) and to 2% for 2019 (vs. 1.75%) and expects the unemployment rate to bottom at 3% in 2020. As a result, some investors are starting to consider that we may see more rate hikes by the Fed than currently expected. With two more hikes priced in for this year and another two to three for 2019, market participants expect the Fed Funds rate to hit [at most] 3.25% by the end of next year, which is more or less in line with the  Fed’s dot plot released at the June meeting (median projection at 3.125% for 2019).

However, we saw that the market is not expecting any more hikes post-2019, which could be interpreted as the end of the tightening cycle by US policymakers. According to the Eurodollar futures market, the December 2019 and December 2020 implied rates are trading equally at 3.06%, which suggests that the US economic outlook is expected to slow down at the end of next year. Hence, an interesting analysis is look at which sectors should perform well within the next 12 to 24 months if we stick with the scenario that economic uncertainty will increase at the end of 2019. A classic strategy looks at the Cyclical vs. the Defensive stocks. The main difference between Cyclical and Defensive stocks is their correlation to the economic cycle; Cyclical stocks tend to do well in periods of economic expansion (relative to Defensive stocks) but tend to experience more losses during recessions. According to empirical research, one of the main aspects that drive Cyclical and Defensive stocks’ performance is the beta of these stocks (also called the market risk premium). As the Defensive stocks are more resilient to an economic downturn, their beta is lower than 1 (resp. higher than 1 for Cyclical stocks).

Therefore, if we take the EuroDollar (ED) Dec19-Dec20 implied rate yield curve as our leading indicator of the business cycle, a flattening yield curve should benefit to the Defensive stocks (vs. Cyclical stocks). However, the chart below tells us a different story (Original Source: Nomura). We looked at the relationship between Cyclical-versus-Defensive sectors and the Dec19-Dec20 ED yield curve since the summer of 2008, and noticed that the two times series have been diverging for the past two years. The yield curve has constantly been flattening during that period, however Cyclical stocks have outperformed Defensive Stocks. We chose Materials, IT and Industrials sectors for the Cyclicals and HealthCare, Telecom and Utilities sectors for the Defensives (Source: Thomson Reuters Total Return Indices), and compute the ratio of the Cyclicals and Defensives new indices (find attached the file).

If you expect the two series to convergence back together, this would imply either a sudden steepening of the yield curve or Cyclicals to underperform Defensives.

Chart: ED Dec19-Dec20 yield curve vs. Cyclical-Defensive stocks (Source: Eikon Retuers)

Sectors vs. YC.PNG

EXCEL DATA LINK ====> Sectors

Great Chart: US 2Y Yield vs. CFTC Specs Positioning

Over the past few weeks, we have noticed an interesting development in the US interest rate market. Since the beginning of the year, the 2-year interest rate has constantly been increasing on the back of a tightening monetary cycle ran by US policymakers; it is now trading at 2.65%, up from 2% in early January. However, the CFTC Commitment of Traders report shows that speculators have not followed the trend and have been reverting their positioning since January (as opposed to the 10Y positioning). As we can see it on the chart, total net specs positions increased from -329K contracts on January 30th to -19K last week (July 17th) on the back of a sharp reduction in shorts from -735K to -492K and some increase in longs (+67K), hence completely diverging from the 2Y yield. What generated this sudden reversal? We think that the rise in the 2Y may be done and that the short end of the curve could settle around the current levels for a while.

After two hikes this year, the Fed Funds rate currently stands at 2%, and another two moves are expected according to market participants for the rest of 2018 (at the September and December meetings). With the US economy expected to grow at 4.5% in real terms in the second quarter according to GDPnow forecasts, US policymakers have benefited from strong momentum in US fundamentals and a dull summer market with the 10Y yield trading quietly below 3% and equities steadily recovering from their February lows. The SP500 index is up 300pts from its low reached on Feb 9th, and currently trades 50pts away from its all-time high reached in January prior the equity rout. Even though financial markets have still got to ‘face’ the August low-liquidity period, which is the most volatile month if we look at the past twenty years, US policymakers have got all the conditions not to disappoint market participants in the following FOMC meetings.

However, we think that much of the action concerning US monetary policy has been priced in by investors, and we can’t see any more hawkish surprises coming in the following months. Therefore, the 2Y may stabilize around its current level at 2.7%, which could explain the reversal in the specs positions. It will be interesting to see how the short-end and the long-end of the curve react to a sudden rise in uncertainty by the end of the summer, pushing down drastically the probability of a hike at the September meeting.

Chart. 2Y US yield vs. CFTC Specs Positioning (Source: Reuters Eikon, CFTC)

Net specs.PNG

Great Chart: Oil Prices vs. Japan Trade Balance

The recovery in oil prices since February 2016 has eased financial conditions for most of the Middle East countries and has reversed the path of the corporate default rate for US energy companies exposed to the shale industry. Higher oil prices have also brought back inflation in most of the economies, hence pushed up expectations of nominal growth rates. However, for countries that are heavy importers of energy (i.e. Japan), higher oil prices usually mean a deterioration of the Trade Balance. Japan has limited domestic proved oil reserves (44 million barrels), which means that the country is a net importer of oil. According to the EIA, Japan is the fourth-largest petroleum consumer and the third largest net importer, and its daily consumption in 2016 was of 4 million barrels per day. Therefore, if we plot the WTI futures prices (6M lead) with the Japanese trade balance, we can notice a significant co-movement between the two times series. This chart suggests that oil prices can be used as a sort of leading indicator for the Japanese trade balance. For instance, when oil prices entered a bear market in 2014, the trade balance switched from a 1.1tr JPY deficit in the middle of 2014 to a 350bn JPY surplus in H2 2016. Hence, with oil prices constantly trending higher with the front-month contract on the WTI trading at $70 per barrel, its highest level since Q4 2014, we can potentially anticipate that the Japanese trade balance will go back into deficit in the medium term.

What are the consequence for the Japanese Yen?

In our BEER FX model, we saw that exchange rates (in log terms) react positively to a positive change in interest rate differential and in terms of trade differential, and negatively to a change in inflation rate differential. Hence, if we expect import prices to rise in Japan due to higher energy costs (especially Oil), the terms of trade should ‘deteriorate’ and therefore have a negative impact on the currency. However, we know that the Japanese Yen is also very sensitive to the current macro environment and often acts as a safe-have asset when the risk-off sentiment rises (Yen appreciates in periods of equity sell-off). In our view, the problem Japanese officials may face in the following 6 months is higher energy prices combined with a strong Yen at 105 (vis-à-vis the US Dollar), which will directly weigh on the country’s economic outlook as fundamentals will start to deteriorate, leaving less and less room for some BoJ manoeuvre.

Chart: Oil prices (WTI, 6M Lead) vs. Japan Trade Balance (Source: Eikon Reuters)

Japan Trade

Great Chart: US Term Premium vs. Business Cycles

Academics and economists have often decomposed the long-term bond yield of a specific country (i.e. US 10Y Treasury) into the sum of the expected path of real interest rate (r*) and the additional term premium, which compensate investors for holding interest rate risk. Two major risks that a bond investor typically face in the long-run are the change in supply of and demand for bonds and the uncertainty around inflation expectations. If the uncertainty increases, the market will demand a higher premium as a response. As the premium is not directly observable, it must be estimated using econometric models. For instance, a popular one that practitioners use is the one developed by Adrian, Crump and Moench (2013), who estimated fitted yields and the expected average short-term interest rates for different maturities (1 to 10 years, see data here).

As you can see, the term premium has been falling since 2009 and is currently negative at -51bps, which has not happened very often. Instead of having a positive term premium for long-term US debt holders carrying interest rate risk, there is actually a discount. The term premium for the 10Y reached an all-time low of -84bps in July 2016, at the same time that the yield on the Treasury reached a record low below 1.40%. However, there are also interest findings when we plot the ACM 10Y term premium with macroeconomic variables. If we overlay it with the US unemployment rate, we can notice a significant co-movement between the two times series. The jobless rate went down from 10% in Q3 2009 to 4.1% in March 2018, tracked by the term premium that fall from roughly 2.5% to -50bps in that same period. In other, it seems that the term premium follows the business cycles, trend lower in periods of positive growth and falling unemployment and rises in periods of contractions. Therefore, for those who are expecting a rise in the US LT yields in the medium term, driven by a reversion in the term premium, what does it mean for the unemployment rate going forward?

Chart. US Unemployment Rate vs. 10Y Term Premium

US Term Pr.png

Source: Reuters Eikon and Adrian et al. (2013)


Great Chart: Term Spread Differentials (US, Germany and Japan)

In this article, we define the term spread of a specific country by the difference between the long-term (10Y) and the short-term (2Y) sovereign yield, which is also referred as the yield curve. As we mentioned it in one of our previous Great Chart articles (here), empirical research has shown a significant relationship between the real economic activity of a country and the yield curve. In today’s edition, we chose to look at the historical developments of the term spread differentials, between the US and Germany and the US and Japan.

Over time, we notice that the term spread has some interesting co-movement with the exchange rate. For instance, between 2005 and 2017, a widening term spread differential between the US and Germany was favourable to the USD/EUR exchange rate (here), meaning that the Euro was appreciating when the US yield curve was steepening more significantly than the German one. However, we saw that the relationship between the two times series broke down in early 2017 and has actually reversed over the past 14 months (here). In other words, based on the current market levels, the 2Y10Y term premium in Germany offers 56bps more than the US. Hence, as the term structure in the US has flattened strongly relative to Germany (yield curve steepened from 50bps in July 2016 to 118bps), the US Dollar depreciated.

This chart shows the evolution of the term spread differentials – between US and Germany and between US and Japan – since 1985. We can observe a strong correlation between the two times series over the past 30 years, with the term spread differential against Germany trading at -57bps, its lowest level since June 2006, and at 42bps against Japan, its lowest level since June 2008, respectively. An interesting observation comes out when we look at the spread between the two TS differentials (US-Japan vs. US-DE), which simply comes back at looking at the cross term spread differential between Germany and Japan. At the exception of the year 1992, the DE-Japan TS differential has always traded between -1% and +1%, and is currently standing at the high of its long-term range. The TS differential currently trades at +1% on the back of a steepening German yield curve since the summer of 2016 (2Y10Y moved from 52bps in July 2016 to 119bps today). It it a good time to play the convergence between the two term structure, i.e going long the German 2Y10Y term spread and short Japan 2Y10Y? The risk of the trade is on Japan side, as shorting the 2Y10Y would imply a steepening yield curve with either the 2Y yield going down or the 10Y rising. With the current BoJ ‘yield curve control’ (YCC) policy, we know that a steepening yield curve in Japan is difficult for the time being, but it will be interesting to see where TS differentials stand in a couple of months.

Chart: Term spread Differentials – Japan and Germany vs. US (Source: Reuters Eikon)

Term Spreads ALl

Great Chart: Italy EPU Index vs. 10Y Bond Yield

The recent results in Italian’s election held on March 4th wasn’t really a surprise for market participants, with EURUSD barely moving (the pair is actually up 2.5 figures over the past week) and the 5Y CDS spread (vs. Germany) flat at around 92bps (here). According to the latest estimates, the populist Five-Star movement, created by comedian Beppe Grillo and led by its prime ministerial candidate Luigi di Maio, came in first individually capturing 32.7% of the votes. However, if we look at the coalitions results, the Center-Right coalition got 37% of the vote shares, with the alliance including the League with 17.4%, former prime minister Silvio Berlusconi’s Forza Italia (14%) and the Brothers of Italy (4.4%) and US with Italy (1.3%) parties. The disappointment was for the Democratic Party, which has governed Italy since 2013, as the Center-Left coalition captured ‘only’ 23% of the vote shares (much lower than the 27+% estimates, here), prompting former PM Matteo Renzi to step down as party leader. The FT published an interesting graphic lately, showing the geography of the electoral vote: Italy, the politically divided country (here). As you can see it, the Five-Star movement made the largest gain in the South (including Sardinia), in regions with the lowest per capita income.

Hence, following the election results, an interesting chart to watch in the weeks to come is the 10Y Bond yield vs. the Italy EPU index. As a reminder, the Economic Policy Uncertainty (EPU) index was developed by Baker, Bloom and Davis (2016) as a measure of economic policy uncertainty based on newspaper coverage frequency. The authors studied the evolution of political uncertainty since 1985 across countries (12 including the US) using leading newspapers that contain a combination of three of the target terms: economy, uncertainty and one or more policy-relevant terms (For the European EPU index, the author used two leading newspapers per country). Since its inception, the index has gained popularity in practice, measuring another form of market’s volatility or uncertainty. Baker et al. found that elevated political uncertainty has negative economic effects, which can potentially impact market prices.

This chart plots the EPU index versus the Italy 10-year bond yield. We can observe an interesting correlation between the two series. Since the financial crisis, it looks like LT sovereign yields have been rising when the EPU index increased ahead of a political or economic uncertain event. For instance, during the European debt crisis of 2010 – 2012, the EPU Index for Italy rose from 75 to over 200, while the 10Y yield skyrocketed from 4% to 7%. The financial meltdown in the Euro area was then halted after ECB Draghi’s “Whatever it takes to preserve the Euro” famous words at a global investment conference in London on 26 July, 2012.

As we mentioned in our previous posts, we don’t see any imminent risk for Italy, however a potential threat to investors would be a prolonged period of political instability. The question now is: can a rise in Italian LT yields in the next few months lead to a contagion to other peripheral countries’ bond yields (i.e. Spain or Portugal, here)?

Chart: Italy EPU Index (lhs) vs. 10 bond yield 

(Source: Eikon Reuters,


The Balassa-Samuelson Effect and The MEVA G10 FX Model

Abstract: In this study, we introduce Danske’s Medium Term FX Evaluation model (MEVA G10 FX), a framework that falls within the class of the Behavioural Equilibrium Exchange Rate (BEER) models. An important concept of the BEER model is that there is no prior theory for the choice of economic variables; hence, the choice of variables is based on economic intuition and data simplicity and availability.

Using two medium-term G10 FX drivers – a gauge of the Balassa-Samuelson effect and the terms of trade – we run a Fixed-Effect panel regression on the G10 currencies, using the US Dollar and the Euro as the base currencies.

PDF LINK ===========================> MEVA G10

EXCEL DATA LINK ====================> MENA FX – Quarterly Data


Results of our study (FX Q1 2018 spot rates were from mid-february) 

Great Chart: US Yield Curve vs. VIX (log, 30M lagged)

As a response to the recent surge in the market’s volatility (VIX), we saw lately an interesting chart that plots the 2Y10Y yield curve overlaid with the VIX (log, 30-month lagged). Even though we don’t necessarily agree with the fact that yield curves are a good predictor of recessions, we like to integrate it in our analysis as a supportive argument when presenting our outlooks as it summarizes a lot of information in a single chart. Previously, we presented the SP500 index versus the 2Y10Y yield curve (here), in which we emphasized that US equities can continue to rise (as the fundamental indicators) for weeks (2000) or months (2006/2007) despite a negative yield curve.

In this chart, we can notice another important factor, which is that the bull momentum in the equity market can persist even though market experiences an increase in price volatility (on an implied base). For instance, in the last two years of the 1990s (98/99), the VIX averaged 25%, 10 percent higher than in the last few years, while the SP500 was up 70% (the Nasdaq actually increased by 100% in the last quarter of 1999).

Hence, if we assume that the 25-year relationship between equity volatility and the business cycle holds on average, the constant flattening US yield curve over the past 2 years was suggesting a rise in the VIX.  The chart shows the persistent divergence between the two times series prior the sell-off; while the 2Y10Y had flattened by 200bps to 0.50% over the past couple of years, the VIX was averaging 10-12. The question now is: what to expect in the future for US equities, volatility and yields?

With the 10-year slowly approaching the 3-percent threshold, are US equities and volatility sensitive to higher long-term yields? As Chris Cole from Artemis pointed out in his memo Volatility and the Alchemy of Risk, there is an estimated 2tr+ USD Global Short Volatility trade (i.e. 1tr USD in risk parity and target vol strategies, 250bn USD in risk premia…). Can we experience another late 1990s period with rising LT yields, higher implied volatility without a global deleveraging impacting all asset prices?

In our view, it is difficult to see a scenario with rising LT yields combined with an elevated volatility (i.e. 20 – 25 %) without a negative impact on overall asset classes. Hence, if we see a persistent high volatility in the medium term as this chart suggests, the deleveraging in both bonds and equities by investment managers will kickstart a negative sell-reinforcing process, creating a significant sell-off in all asset classes with important outflows in the high-yield / EM investment world, hence leading to a repricing of risk.

Chart. US 2Y10Y Yield Curve vs. VIX (log, 30M lagged) (Source: Eikon Reuters)

USYield vs VIX

Great Chart: Relative Implied Volatility – VIX/RVX ratio

For each investor, there are several ways of measuring the market’s temperature. For instance, former Fed chairman Alan Greenspan would look at the 10-year US yield, some investment managers will simply look at the VIX and currency traders will tend to watch the moves on the Japanese Yen, especially against the US and Australian Dollar (see AUDJPY and SP500 correlation here). We know empirically that a sudden move on the Yen (JPY appreciates relative to other currencies) is usually accompanied with an equity correction and hence an increase in the implied volatility. Even though we hear a lot about the VIX measure, we also need to pay attention to the implied volatility surface, presenting skew/smiles features and term structure, and compare it relative to other equity markets and asset classes. For instance, a couple of measures we like to watch are the VIX/Skew (here) and the VIX/VXV (here) ratios.

Hence, in today’s article, we present the VIX/RVX, which measures the ratio between the implied volatility of the SP500 and the Russell 2000, a small-cap stock market index. As you may know, the ‘small cap premium’ has been a crowded study in the empirical academic research, which started from the early work of Rolf Banz (1981) who founded that ‘smaller firms have had higher risk-adjust returns, on average, than larger firms’. Then, in their paper The Cross-Section of Expected Stock Returns (1992), Fama and French found that value and small cap stocks, on average, outperform growth and large carp stocks. As you can see it on the chart, an interesting development has occurred over the past few days following the huge spike in volatility. The VIX/RVX, which has constantly been above parity since 2006, is now sitting at 0.83. In other words, according to the index, the Russell 2000 equity market carries less risk than the SP500. The question now is: what explains this sudden drop in the ratio?

If we look at the week-on-week change in both indexes, we can first notice that, at current levels, the WoW change of 11.6 in the VIX came in at 5th position in the index history, just a 0.3 ‘shy’ of the October 1997 move (here). However, if we now look at the change in the implied volatility of the small caps, the RVX index barely changed (+2.3) over the past week, meaning that the drop in the ratio was only coming from the VIX move (here).

Hence, this leads us to an interesting conclusion: it seems that there is much more financialization going on with the VIX than with the RVX, either through the creation of single and double-levered long and short VIX ETFs products, or from a volatility-targeting and risk-parity perspectives (are those strategies more oriented towards the SP500?).

Chart: Relative Implied Volatility – VIX / RBX ratio (Source: Eikon Reuters)